Low-power high-speed rail-to-rail LCD output buffer with dual-path push–pull operation and quiescent current control

The present paper addresses a new compact low-power high-speed output buffer amplifier topology for large-size liquid crystal display applications. The suggested buffer achieves fast driving performance, draws a low quiescent current during static operation and offers a rail-to-rail common-mode input range. The circuit provides enhanced slewing capabilities with a limited power consumption by simultaneously exploiting the push–pull output sections of two basic complementary-type input amplifiers to realize a dual-path push–pull operation of the output stage. An auxiliary biasing network integrated in the input differential stage allows the quiescent bias conditions of the class-AB output stage to be inherently controlled without additional current dissipation. Post-layout simulation results confirm that the proposed amplifier can drive a 1-nF column line load within a 0.9-μs settling time under a 3-V full voltage swing, while drawing only 3.5-μA quiescent current. Monte Carlo simulations are finally carried out, showing a good degree of robustness of the proposed output buffer against process and mismatch variations.     

Ketoprofen Spray-dried Microspheres Based on Eudragit® RS and RL: Study of the Manufacturing Parameters

The preparation of ketoprofen spray-dried microspheres can be affected by the long drug recrystallization time. Polymer type and drug–polymer ratio as well as manufacturing parameters affect the preparation. The purpose of this work was to evaluate the possibility to obtain ketoprofen spray-dried microspheres using the Eudragit® RS and RL; the influence of the spray-drying parameters on morphology, dimension, and physical stability of microspheres was studied. Ketoprofen microspheres based on Eudragit® blend can be prepared by spray-drying and the nebulization parameters do not influence significantly particle properties; nevertheless, they can be affected by drying and storage methods. No effect of the container material is found.     

Analysis of distorted unbalanced waveforms in inverter drives

A new method is proposed for the analysis of waveforms in a three-phase system when both distortion and unbalance are present. The method makes it possible to obtain the positive and negative-sequence components of each harmonic system present in the three phases. This method provides a way to get information both on the degree of unbalance and on the distortion factors of the waveforms generated by pulsewidth-modulated inverters supplying induction motors     

An energetic approach to the analysis of anisotropic hyperelastic materials

We demonstrate that for the class of anisotropic hyperelastic materials with stiffening behaviour (i.e., the stiffness increases for increasing strain), it is possible to find an approximation by means of the linear superposition of an anisotropic quadratic potential, generated by the true linear elasticity tensor of the target material, and a suitable correction potential that is isotropic and hyperelastic. The proposed method can be implemented into commercially available Finite Element software by use of featured options only. This approach is intended to provide the solution to a stress-strain problem, based entirely on energetic considerations, which ensures the convexity of the potentials, and provides a simple material characterisation procedure.     

Selection of catalytically active biotin ligase and trypsin mutants by phage display

Phage display has been shown to facilitate greatly the selectionof polypeptides with desired properties by establishing a directlink between the polypeptide and the gene that encodes it. However,selection for catalytic activities displayed on phage remainsa challenge, since reaction products diffuse away from the enzymeand make it difficult to recover catalytically active phage–enzymes.We have recently described a selection methodology in whichthe reaction substrate (and eventually the reaction product)is anchored on calmodulin-tagged phage–enzymes by meansof a calmodulin binding peptide. Phage displaying a catalyticactivity are physically isolated by means of affinity reagentsspecific for the product of reaction. In this study, we investigatedthe efficiency of selection for catalysis by phage display,using a ligase (the Escherichia coli biotin ligase BirA) andan endopeptidase (the rat trypsin His57     

Analgesic,Anxiolytic and Anaesthetic Effects of Melatonin: New Potential Uses in Pediatrics

Exogenous melatonin is used in a number of situations, first and foremost in the treatment of sleep disorders and jet leg. However, the hypnotic, antinociceptive, and anticonvulsant properties of melatonin endow this neurohormone with the profile of a drug that modulates effects of anesthetic agents, supporting its potential use at different stages during anesthetic procedures, in both adults and children. In light of these properties, melatonin has been administered to children undergoing diagnostic procedures requiring sedation or general anesthesia, such as magnetic resonance imaging, auditory brainstem response tests and electroencephalogram. Controversial data support the use of melatonin as anxiolytic and antinociceptive agents in pediatric patients undergoing surgery. The aim of this review was to evaluate available evidence relating to efficacy and safety of melatonin as an analgesic and as a sedative agent in children. Melatonin and its analogs may have a role in antinociceptive therapies and as an alternative to midazolam in premedication of adults and children, although its effectiveness is still controversial and available data are clearly incomplete.     

A spectro-microscopic investigation of Fe-Co bimetallic catalysts supported on MgO for the production of thin carbon nanotubes

Fe-Co bimetallic catalysts supported on MgO were studied for the catalytic chemical vapor deposition growth of carbon nanotubes (CNTs). Different wt.% metal loadings were investigated at various deposition temperatures and times. Characterization of the products involved thermal analysis (DTA-TGA), X-ray diffraction, spectroscopy (Raman, UPS, EELS and STS) and microscopy (SEM, TEM and STM) techniques. It was found that the metal content is critical, not only to the yield and the structural quality of the synthesized carbon nanotubes, but it can be also used to tune the desired type of synthesized nanotubes. Lower (2 wt.%) loadings of Fe-Co catalysts favor the formation of single- and/or double-wall CNTs for deposition time and temperature 30 min and 800 °C, respectively. Thermal analysis and Raman measurements showed that these thin CNTs were synthesized at high amounts (CNT-per-catalyst wt.% of more than 100%), exhibiting high graphitization degree with only traces of by-products (mainly amorphous carbon) among them. Microscopy results revealed the formation of CNTs bundles, consisting of individual nanotubes with less than 2 nm outer diameter, while additional energy loss measurements pointed out that the deposited CNTs are mainly single wall. Higher (10 wt.%) Fe-Co loadings resulted to the formation of multi-wall CNTs.     

Identification of IPMC nonlinear model via single and multi-objective optimization algorithms

Ionic Polymer–Metal Composites (IPMCs) are electro-active polymers transforming mechanical forces into electric signals and vice versa. This paper proposes an improved electro-mechanical grey-box model for IPMC membrane working as actuator. In particular the IPMC nonlinearity has been characterized through experimentation and included within the electric model. Moreover identification of the model parameters has been performed via optimization algorithms using both single- and multi-objective formulation. Minimization was attained via the Nelder–Mead simplex and the Genetic Algorithms considering as cost functions the error between the experimental and modeled absorbed current and the error between experimental and modeled displacement. The obtained results for the different formulations have been then compared.     

SCIDDICA-SS3: a new version of cellular automata model for simulating fast moving landslides

Cellular Automata (CA) are discrete and parallel computational models useful for simulating dynamic systems that evolve on the basis on local interactions. Some natural events, such as some types of landslides, fall into this type of phenomena and lend themselves well to be simulated with this approach. This paper describes the latest version of the SCIDDICA CA family models, specifically developed to simulate debris-flows type landslides. The latest model of the family, named SCIDDICA-SS₃, inherits all the features of its predecessor, SCIDDICA-SS₂, with the addition of a particular strategy to manage momentum. The introduction of the latter permits a better approximation of inertial effects that characterize some rapid debris flows. First simulations attempts of real landslides with SCIDDICA-SS₃ have produced quite satisfactory results, comparable with the previous model.     

Selection of a representative value function in robust multiple criteria sorting

We introduce the concept of a representative value function in robust ordinal regression applied to multiple criteria sorting problems. The proposed approach can be seen as an extension of UTADIS^GMS, a new multiple criteria sorting method that aims at assigning actions to p pre-defined and ordered classes. The preference information supplied by the decision maker (DM) is composed of desired assignments of some reference actions to one or several contiguous classes—they are called assignment examples. The robust ordinal regression builds a set of general additive value functions compatible with the assignment examples and results in two assignments: necessary and possible. The necessary assignment specifies the range of classes to which the action can be assigned considering all compatible value functions simultaneously. The possible assignment specifies, in turn, the range of classes to which the action can be assigned considering any compatible value function individually. In this paper, we propose a way of selecting a representative value function among the set of compatible ones. We identify a few targets which build on results of the robust ordinal regression and could be attained by a representative value function. They concern enhancement of differences between possible assignments of two actions. In this way, the selected function highlights the most stable part of the robust sorting, and can be perceived as representative in the sense of robustness preoccupation. We envisage two possible uses of the representative value function in decision support systems. The first one is an explicit exhibition of the function along with the results of the UTADIS^GMS method, in order to help the DM to understand the robust sorting. The other is an autonomous use, in order to supply the DM with sorting obtained by an example-based procedure driven by the chosen function. Three case studies illustrating the use of a representative value function in real-world decision problems are presented. One of those studies is devoted to the comparison of the introduced concept of representativeness with alternative procedures for determining a single value function, which we adapted to sorting problems, because they were originally proposed for ranking problems.